ROHCMar 7, 2017

Effects of Faults, Experience, and Personality on Trust in a Robot Co-Worker

arXiv:1703.02335v226 citations
Originality Synthesis-oriented
AI Analysis

This work provides incremental insights for robot designers to enhance trust in human-robot interactions, specifically in manufacturing contexts.

The study investigated factors affecting trust in a robot co-worker in a collaborative manufacturing scenario, finding that robot faults did not significantly impact human perceptions, while personality and previous experience had small effects.

To design trustworthy robots, we need to understand the impact factors of trust: people's attitudes, experience, and characteristics; the robot's physical design, reliability, and performance; a task's specification and the circumstances under which it is to be performed, e.g. at leisure or under time pressure. As robots are used for a wide variety of tasks and applications, robot designers ought to be provided with evidence and guidance, to inform their decisions to achieve safe, trustworthy and efficient human-robot interactions. In this work, the impact factors of trust in a collaborative manufacturing scenario are studied by conducting an experiment with a real robot and participants where a physical object was assembled and then disassembled. Objective and subjective measures were employed to evaluate the development of trust, under faulty and non-faulty robot conditions, and the effect of previous experience with robots, and personality traits. Our findings highlight differences when compared to other, more social, scenarios with robotic assistants (such as a home care assistant), in that the condition (faulty or not) does not have a significant impact on the human's perception of the robot in terms of human-likeliness, likeability, trustworthiness, and even competence. However, personality and previous experience do have an effect on how the robot is perceived by participants, even though that is relatively small.

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